Biology subjects

Kobayashi, J.

Publications and source records attributed to Kobayashi, J..

10 recordsLinked to original sources

bioRxiv2026

Precision-Controlled Active Inference Accounts for Sensory Reweighting in Quiet Standing

Human quiet standing relies on vestibular, proprioceptive, and visual information whose contributions change with sensory context. Dynamic posturography characterizes this reweighting through responses to visual-scene and support-surface perturbations, but a compact mathematical account of how sensory reliability propagates from state estimation to postural action remains incomplete. We develop a minimal quiet-standing model in which sensory reliability is encoded by channel-specific precision parameters that weight sensory prediction errors. A one-link inverted pendulum receives vestibular, proprioceptive, and visual observations, estimates posture using an active-inference variational free-energy objective over temporally embedded states, and selects ankle torque by minimizing the same free-energy form under an upright sensory goal. Changes in sensory conditions enter the model only through the relative channel precisions; body dynamics, the action optimizer, and the upright goal prior are held fixed. A fixed-point analysis yields closed-form predictions: the perturbation-induced belief bias, each channels state-update contribution, and the resulting posture shifts are set by relative channel precisions, with a stability condition on the upright goal. Closed-loop simulations confirmed these predictions: reducing an unreliable channels precision reduced perturbation-driven postural shifts by approximately 82%, as predicted, with a matching decrease in that channels state-update contribution, identifying belief updating as the mechanism of reweighting. A graded reliability-to-precision mapping monotonically controlled sensory contribution, and reweighting required relative, channel-selective precision changes rather than a global reduction. These results provide a compact mathematical account of postural sensory reweighting as relative, context-selective precision control in a closed-loop multisensory system.

neuroscience↗

bioRxiv2026

Reach-and-hold at a musculoskeletal arm posture is an unstable-equilibrium stabilization problem: the limits of fixed equilibrium-point and impedance controllers

Holding a redundant limb at a commanded posture against gravity is a basic problem in musculoskeletal motor control. Whether fixed, biologically grounded controllers can achieve it remains unclear. Using the MyoSuite myoArm under a frozen-criterion, hash-provenanced protocol, we evaluate fixed, non-learning controllers: an equilibrium-point/referent (lambda) reflex, a reflex with co-contraction, an endpoint Cartesian impedance controller, a gravity-compensation feedforward, and an exact inverse-statics gravity-balancing command. None achieves a stable near-task hold. The tested referent reflex placed a near-target equilibrium (best 0.048 m at the lowest target), but sustained a structural limit cycle that velocity damping did not cure; endpoint impedance settled at far false equilibria; and an exact gravity-balancing activation can exist while deployment falls away. At posture-matched targets evaluated in both the 34- and 63-muscle models, the reduced acceleration-position Jacobian has positive real eigenvalues, indicating locally unstable second-order modes. In the 34-muscle model, the full fixed-controller grid also fails to produce a stable near-task hold. In the 63-muscle model, measured endpoint stiffness spans human-scale magnitudes and human-like ellipse axis ratios across a co-contraction sweep, so the failure is not explained by a limp or non-biological plant. We conclude that reach-and-hold is an unstable-dynamics stabilization problem: the tested fixed equilibrium-point/referent controller can place a near-target equilibrium, but does not stabilize it. These results motivate learned selective impedance and predictive/internal-model control as the next class of mechanisms, separating equilibrium placement from stabilization.

neuroscience↗

bioRxiv2026

Climbing-fiber-like online readout adaptation in frozen continuous-time networks reproduces force-field adaptation and after-effects

Robotic motor control built on liquid neural networks and related continuous-time models, such as LTC and CfC, is typically trained offline via backpropagation through time and lacks an explicit mechanism for recalibrating online as plant dynamics change. We ask whether a frozen CfC core, whose liquid state spans a fixed continuous-time basis, can support cerebellar-style online adaptation by adapting only its linear read-out with a climbing-fiber-like error signal. In a planar two-link reaching simulation with a velocity-dependent curl force field, we adapt the readout online with a feedback-error-learning (FEL) signal under a least-mean-squares (LMS) rule, leaving the core un-touched. The frozen-core readout-only controller re-straightens curl-perturbed reaches and, upon field removal, produces a mirror-image after-effect--a behavioral signature consistent with internal-model learning--that a feedback-only controller does not produce. The result generalizes from a dense CfC to a sparse Neural-Circuit-Policy (NCP) wiring when the recurrent state, rather than the projected motor output, is used as the readout basis; it is robust to force-field strength and direction; and a recursive-least-squares variant adapts faster but de-adapts slowly because its covariance collapses, a rigidity that a covariance-reset safe-forgetting rule removes. Within the explored two-link planar simulation range, we did not find a readout-only failure case that required adapting the frozen core in the tested conditions. In this simulation study, adapting only the readout therefore provides a biologically inspired, low-cost online error-adaptation layer for offline-trained continuous-time controllers.

neuroscience↗

bioRxiv2026

Reliability-weighted target-position estimation in a musculoskeletal arm model: adaptive priors and learned source weighting under violations of fixed-precision assumptions

Reliability-weighted integration is a normative account of cue combination, but its scope in musculoskeletal models and conditions requiring adaptive or learned extensions remains unclear. We studied target-position estimation in a MyoSuite arm within a field-wise architecture representing vision, proprioception, forward prediction, and a task prior. Target-position experiments combined vision, forward prediction, and, where applicable, the task prior by precision weighting; proprioception informed other state fields. At the open-loop state-estimate level, a trusted but wrong prior biased the target estimate more as visual reliability decreased, and a false visual cue was followed under low noise and discounted under high noise; both effects followed the bias{approx} w {middle dot} offset pattern. Across trials, an adaptive prior tracked shifts in the target mean, while variance tracking reduced the prior weight as the target spread increased. A learned softmax integrator met the prespecified parity criterion relative to precision weighting for calibrated Gaussian synthetic observation channels and improved estimation when reported variance was miscalibrated, or channel errors were biased, heavy-tailed, or correlated. On target-position observations from two held-out MyoSuite rollout seeds, improvements under prediction miscalibration and injected visual outliers were directionally consistent across seeds during offline replay. The MSE benefit in the outlier regime reflected regime-level source weighting rather than consistent per-trial outlier detection. These results define a computational boundary: precision weighting was sufficient in the calibrated conditions tested here, whereas adaptive statistics or learned source weighting became useful when assumptions changed or failed. Evidence from the arm model is limited to target-position estimates; endpoint propagation remains unresolved.

neuroscience↗

bioRxiv2026

How a Predictive State Observer Can Self-Adapt Its Sensory Prediction-Error Correction Gain: Closed-Loop Evidence from a Muscle-Driven Reaching Task

We ask how a forward-model-based predictive state observer should set its sensory prediction-error correction gain during muscle-driven reaching, and whether that gain can be adapted from agent-available signals -- innovation history and per-episode reaching outcome -- rather than from swept oracle labels. We evaluate a residual-MLP forward model in a 34-muscle MyoSuite arm on an IK-reachable below-shoulder task, deployed in closed loop with a stabilized endpoint probe controller that uses non-negative least-squares muscle routing and a virtual target ramp; the controller is a stabilized probe for evaluating state-estimation effects, not a biological motor planner. A swept fixed-gain closed-loop oracle reveals a delay-dependent correction structure: with no sensory delay, intermediate correction gains are best (K = 0.25-0.50), whereas with 18-step delay observation-heavy correction wins (K = 1.0). The forward-model-only K = 0 ablation is not the oracle: it is systematically worse than the best fixed K by 1.9-6.1 cm and shows large NNLS controller residuals caused by long-horizon autoregressive drift; we therefore report K = 0 as a diagnostic. Outcome-trained reliability-adaptive observers improve the delayed regime by 1.9-2.5 cm over default reliability while remaining neutral in no-delay cells, where the oracle is already intermediate. A feature-conditioned {beta} adapter that maps cell-level innovation statistics to per-field gain parameters nearly matches a per-cell trained diagnostic in 5/6 cells, but both remain 1.4-1.8 cm worse than the swept fixed-K oracle at 18-step delay. These results separate the delay-dependent correction structure, the forward-model-only failure mode of K = 0, and the remaining limits of agent-available adaptive correction.

neuroscience↗

bioRxiv2026

Intramuscular adrenaline administration does not improve a survival period on rats with crush syndrome despite short-term hemodynamic support and renal protection

Crush syndrome (CS) is a serious medical condition characterized by damage to the muscle cells due to pressure and is associated with high mortality, even in patients receiving fluid therapy. We focused on adrenaline (Adr), a standard medication administered by medical teams dispatched during disasters. Adr is readily available for use in disaster scenarios owing to its inclusion in standard emergency kits. The effectiveness of Adr in the treatment of CS remains a subject of ongoing debate. This study aimed to evaluate the impact of Adr on acute complications, such as heart failure, shock, and renal failure, and explore whether its influence on inflammatory pathways is correlated with improved survival in rats with CS. The CS model involved subjecting anesthetized rats to bilateral hindlimb compression using a rubber tourniquet for 5 h. Subsequently, the rats were randomly divided into eight groups. Under continuous monitoring and recording of the arterial blood pressure, blood and tissue samples were collected for biochemical analyses at designated time points before and after reperfusion. The survival rate, vital signs, and blood gas parameters were higher in the CS group than in the sham group. They were improved in the Adr-treated group (0.01 or 0.01 mg/kg), which was not significantly different from that in the CS group, despite the improvement in shock and kidney dysfunction. In conclusion, intramuscular Adr provides immediate hemodynamic stabilization and renal protection during the early stages of CS. However, its use requires careful dose titration; low doses may promote the systemic release of lethal toxins, whereas high doses may worsen metabolic acidosis. These findings highlight the importance of combining Adr with other therapies, such as fluid resuscitation, to manage systemic toxemia inherent in CS.

pharmacology and toxicology↗

bioRxiv2026

Decoupling smoothness, accuracy, and kinematic invariance in biological reach: an ablation study of an equilibrium-point controller in a 34-muscle arm model

Withdrawal statementThe authors have withdrawn this manuscript because, after submission, a methodological flaw was identified in the kinematic lambda recipe used by the controller: it does not include a gravity-compensation term. As a consequence, all controller variants converge toward a similar end-region of the workspace regardless of the commanded target, so the reported minimum-tip-error values ([~]100 mm) and the equivalence and non-inferiority conclusions relative to the endpoint-PD + spinal baseline reflect workspace geometry rather than reaching performance. The central comparison and the main conclusions of the paper are therefore not supported by the underlying experiments. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

neuroscience↗

bioRxiv2026

Inhaled nitric oxide as a rescue therapy in rat crush syndrome: translating bench research to field application

Crush syndrome (CS) is characterised by ischaemia/reperfusion-induced rhabdomyolysis, leading to systemic inflammation and high mortality. Building on our previous findings that intravenous nitric oxide (NO) donors improve survival in this condition, we investigated the therapeutic efficacy of inhaled NO delivered via a portable, controlled-release device in an experimental rat model of CS. Anaesthetised rats underwent bilateral hindlimb compression using rubber tourniquets for 5 h, followed by reperfusion. Among the various inhalation conditions tested, administration of NO (160 parts per million) for 2 h after reperfusion significantly increased survival rate from 20 to 90%. Improvements in haemodynamic parameters, biochemical markers, and histopathological findings correlated with enhanced survival outcomes. These results suggest that on-site NO inhalation therapy may serve as an effective first-line, emergency intervention for CS, particularly in disaster settings. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/710439v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1368bb5org.highwire.dtl.DTLVardef@e3da0org.highwire.dtl.DTLVardef@efe1c3org.highwire.dtl.DTLVardef@cf000e_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2022

Deleterious mutations in a heterozygous chromosome result in recessive lethality in silkworm semiconsomic strains

In this study, we found two embryonic lethal mutations, t04 lethal (l-t04) and m04 lethal (l-m04), in semiconsomic strains T04 and M04, respectively. In these semiconsomic strains, the entire diploid genome, except for one chromosome 4 of the wild silkworm Bombyx mandarina, is substituted with chromosomes of the domesticated silkworm B. mori, and l-t04 and l-m04 mutations are located on B. mandarina-derived chromosome 4. The mutations responsible for the l-t04 and l-m04 were identified as the Bombyx homolog of imaginal discs arrested (Bmida) and TATA Box Binding Protein-associated factor 5 (BmTaf5), respectively. These findings indicate that both mutations were independently introduced during or after the development of semiconsomic strains. We conclude that the recessive embryonic lethality in the T04 and M04 strains is due to deleterious mutations produced in B. mandarina-derived chromosome 4. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/521575v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1c59ea3org.highwire.dtl.DTLVardef@131fbf0org.highwire.dtl.DTLVardef@93515borg.highwire.dtl.DTLVardef@1c23afe_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2022

Use of the particle agglutination/particle agglutination-inhibition test for antigenic analysis of SARS-CoV-2

The antigenicity of SARS-CoV-2 is a critical issue for the effectiveness of the vaccine, and thus it should be phenotypically evaluated by serological assays as new field isolates emerge. The hemagglutination/hemagglutination-inhibition (HA/HI) tests are well-known as a representative method for antigenic analysis of influenza viruses, but SARS-CoV-2 is unlikely to agglutinate to human or guinea pig red blood cells. Therefore, the antigenic analysis requires complicated enzyme-linked immunosorbent assay (ELISA) or cell-based assays such as the microneutralization assay. In this study, we developed the particle agglutination/particle agglutination-inhibition (PA/PAI) test to easily and rapidly quantify the virus and antibody using human angiotensin-converting enzyme 2 (hACE2)-bound latex beads. The PA titer was positively correlated with the plaque-forming units. The PAI titer using post-infection Syrian hamster antisera clearly revealed the antigenic difference between the omicron and previous variants. The results show the PAI test is useful for easy and rapid antigenic analysis of SARS-CoV-2.

microbiology↗